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                    ECCV 2016 Hydra CCNN
            
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                    线性模型
            
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                    神经网络
            
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                    支持向量机
            
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                    贝叶斯分类器
            
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                    集成学习
            
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                    聚类
            
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                    降维与度量学习
            
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                    特征选择与稀疏学习
            
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                    计算学习理论
            
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                    半监督学习
            
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                    概率图模型
            
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                    规则学习
            
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                    强化学习
            
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                    附录
            
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                                <h1 id="&#x7EBF;&#x6027;&#x6A21;&#x578B;">&#x7EBF;&#x6027;&#x6A21;&#x578B;</h1>
<h2 id="&#x7B2C;3&#x7AE0;-&#x7EBF;&#x6027;&#x6A21;&#x578B;">&#x7B2C;3&#x7AE0; &#x7EBF;&#x6027;&#x6A21;&#x578B;</h2>
<ul>
<li><p>Page53: &#x7EBF;&#x6027;&#x56DE;&#x5F52;(252)(linear regression)</p>
<p>&#x7ED9;&#x5B9A;&#x6570;&#x636E;&#x96C6;<script type="math/tex; ">D={(x_i,y_i)...}</script>&#xFF0C;&#x7EBF;&#x6027;&#x56DE;&#x5F52;&#x8BD5;&#x56FE;&#x5B66;&#x5F97;&#x4E00;&#x4E2A;&#x7EBF;&#x6027;&#x6A21;&#x578B;&#x4EE5;&#x5C3D;&#x53EF;&#x80FD;&#x51C6;&#x786E;&#x5730;&#x9884;&#x6D4B;&#x5B9E;&#x503C;&#x8F93;&#x51FA;&#x6807;&#x8BB0;</p>
</li>
<li><p>Page53: &#x7EBF;&#x6027;&#x6A21;&#x578B;(linear model)</p>
<p>&#x7ED9;&#x5B9A;&#x7531;d&#x4E2A;&#x5C5E;&#x6027;&#x63CF;&#x8FF0;&#x7684;&#x793A;&#x4F8B;<script type="math/tex; ">x=(x_1;x_2;...x_d)</script>&#xFF0C;<script type="math/tex; ">x_i</script>&#x662F;x&#x5728;&#x7B2C;i&#x4E2A;&#x5C5E;&#x6027;&#x4E0A;&#x7684;&#x53D6;&#x503C;&#xFF0C;&#x7EBF;&#x6027;&#x6A21;&#x578B;&#x8BD5;&#x56FE;&#x5B66;&#x5F97;&#x4E00;&#x4E2A;&#x901A;&#x8FC7;&#x5C5E;&#x6027;&#x7684;&#x7EBF;&#x6027;&#x7EC4;&#x5408;&#x6765;&#x8FDB;&#x884C;&#x9884;&#x6D4B;&#x7684;&#x51FD;&#x6570;&#xFF0C;&#x5373;</p>
<p><script type="math/tex; ">f(x) = w_1x_1+w_2x_2+...+w_dx_d+b</script></p>
</li>
<li><p>Page54: &#x53C2;&#x6570;&#x5B66;&#x4E60;</p>
<p>&#x7EBF;&#x6027;&#x56DE;&#x5F52;&#x8BD5;&#x56FE;&#x5B66;&#x5F97;<script type="math/tex; ">f(x_i) = wx_i + b</script>, &#x4F7F;&#x5F97;<script type="math/tex; ">f(x_i) \approx y_i</script></p>
</li>
<li><p>Page54: &#x5E73;&#x65B9;&#x635F;&#x5931;</p>
<p>&#x6B27;&#x6C0F;&#x8DDD;&#x79BB;&#x7B97;&#x5F97;&#x7684;&#x5747;&#x65B9;&#x8BEF;&#x5DEE;</p>
</li>
<li><p>Page54: &#x6700;&#x5C0F;&#x4E8C;&#x4E58;&#x6CD5;(72)(least square method)</p>
<p>&#x57FA;&#x4E8E;&#x5747;&#x65B9;&#x8BEF;&#x5DEE;&#x6700;&#x5C0F;&#x5316;&#x6765;&#x8FDB;&#x884C;&#x6A21;&#x578B;&#x6C42;&#x89E3;&#x7684;&#x65B9;&#x6CD5;&#x79F0;&#x4E3A;&#x6700;&#x5C0F;&#x4E8C;&#x4E58;&#x6CD5;</p>
</li>
<li><p>Page55: &#x591A;&#x5143;&#x7EBF;&#x6027;&#x56DE;&#x5F52;(multivariate linear regression)</p>
<p>&#x6837;&#x672C;&#x7531;&#x591A;&#x4E2A;&#x5C5E;&#x6027;&#x63CF;&#x8FF0;&#x7684;&#x7EBF;&#x6027;&#x56DE;&#x5F52;</p>
</li>
<li><p>Page56: &#x5BF9;&#x6570;&#x7EBF;&#x6027;&#x56DE;&#x5F52;(log-linear regression)</p>
<p>&#x7EBF;&#x6027;&#x56DE;&#x5F52;&#x7684;&#x4E00;&#x79CD;&#x53D8;&#x5316;&#xFF0C;<script type="math/tex; ">ln y=wx+b</script></p>
</li>
<li><p>Page56: &#x6B63;&#x5219;&#x5316;(105,133)&#xFF08;regularization&#xFF09;</p>
<p>&#x5F80;&#x5F80;&#x53EF;&#x4EE5;&#x89E3;&#x51FA;&#x591A;&#x4E2A;w&#x90FD;&#x80FD;&#x4F7F;&#x5747;&#x65B9;&#x8BEF;&#x5DEE;&#x6700;&#x5C0F;&#x5316;&#xFF0C;&#x9009;&#x62E9;&#x54EA;&#x4E00;&#x4E2A;&#x89E3;&#x5C06;&#x7531;&#x5B66;&#x4E60;&#x7B97;&#x6CD5;&#x7684;&#x5F52;&#x7EB3;&#x504F;&#x597D;&#x51B3;&#x5B9A;&#xFF0C;&#x5E38;&#x89C1;&#x7684;&#x505A;&#x6CD5;&#x662F;&#x5F15;&#x5165;&#x6B63;&#x5219;&#x5316;&#x9879;&#x3002;</p>
</li>
<li><p>Page57: &#x5BF9;&#x6570;&#x51E0;&#x7387;&#x56DE;&#x5F52;&#xFF08;log-linear regression&#xFF09;</p>
<p>&#x5BF9;&#x4E8E;&#x5206;&#x7C7B;&#x95EE;&#x9898;&#xFF0C;&#x9700;&#x8981;&#x627E;&#x4E00;&#x4E2A;&#x5355;&#x8C03;&#x53EF;&#x5FAE;&#x51FD;&#x6570;&#x5C06;&#x6570;&#x636E;&#x548C;&#x7EBF;&#x6027;&#x6A21;&#x578B;&#x5173;&#x8054;&#x8D77;&#x6765;&#xFF0C;&#x5355;&#x4F4D;&#x9636;&#x8DC3;&#x51FD;&#x6570;&#x4E0D;&#x8FDE;&#x7EED;&#xFF0C;&#x5BF9;&#x6570;&#x51E0;&#x7387;&#x51FD;&#x6570;&#x5219;&#x8FDE;&#x7EED;&#x4E14;&#x5355;&#x8C03;&#x53EF;&#x5FAE;&#xFF0C;&#x5E76;&#x8FD1;&#x4F3C;&#x5355;&#x4F4D;&#x9636;&#x8DC3;&#x51FD;&#x6570;</p>
<p><script type="math/tex; ">y = 1/(1+e^{-z})</script></p>
<p>&#x7528;&#x7EBF;&#x6027;&#x56DE;&#x5F52;&#x6A21;&#x578B;&#x7684;&#x9884;&#x6D4B;&#x7ED3;&#x679C;&#x53BB;&#x903C;&#x8FD1;&#x771F;&#x5B9E;&#x6807;&#x8BB0;&#x7684;&#x5BF9;&#x6570;&#x51E0;&#x7387;&#xFF0C;&#x56E0;&#x6B64;&#x5BF9;&#x5E94;&#x7684;&#x6A21;&#x578B;&#x79F0;&#x4E3A;&#x201C;&#x5BF9;&#x6570;&#x51E0;&#x7387;&#x56DE;&#x5F52;&#x201D;&#x3002;</p>
</li>
<li><p>Page57: &#x5E7F;&#x4E49;&#x7EBF;&#x6027;&#x6A21;&#x578B;&#xFF08;generalized linear model&#xFF09;</p>
<p>&#x8003;&#x8651;&#x5355;&#x8C03;&#x53EF;&#x5FAE;&#x51FD;&#x6570;g(.)&#xFF0C;&#x4EE4; y=g(wx+b)&#xFF0C;&#x8FD9;&#x6837;&#x5F97;&#x5230;&#x7684;&#x6A21;&#x578B;&#x79F0;&#x4E3A;&#x5E7F;&#x4E49;&#x7EBF;&#x6027;&#x6A21;&#x578B;&#xFF0C;&#x5176;&#x4E2D;&#x51FD;&#x6570;g&#x79F0;&#x4E3A;&#x8054;&#x7CFB;&#x51FD;&#x6570;&#x3002;</p>
</li>
<li><p>Page57: &#x9636;&#x8DC3;&#x51FD;&#x6570;(98)&#xFF08;unit-step function&#xFF09;</p>
<p>&#x8003;&#x8651;&#x4E8C;&#x5206;&#x7C7B;&#x4EFB;&#x52A1;&#xFF0C;&#x6211;&#x4EEC;&#x9700;&#x8981;&#x5C06;&#x5B9E;&#x503C;z&#x8F6C;&#x4E3A;0/1&#x503C;&#xFF0C;&#x6700;&#x7406;&#x60F3;&#x7684;&#x662F;&#x5355;&#x4F4D;&#x9636;&#x8DC3;&#x51FD;&#x6570;&#xFF1A; <script type="math/tex; ">\begin{eqnarray}y= \begin{cases} 0, &z<0\cr 0.5, &z=0 \cr 1, &1\end{cases} \end{eqnarray}</script></p>
</li>
<li><p>Page57: &#x8054;&#x7CFB;&#x51FD;&#x6570;(link function)</p>
<p>&#x89C1;&#x5E7F;&#x4E49;&#x7EBF;&#x6027;&#x6A21;&#x578B;</p>
</li>
<li><p>Page58: Sigmoid&#x51FD;&#x6570;(98,102)</p>
<p>Sigmoid&#x51FD;&#x6570;&#x5373;&#x5F62;&#x4F3C;S&#x7684;&#x51FD;&#x6570;</p>
</li>
<li><p>Page58: &#x5BF9;&#x7387;&#x51FD;&#x6570;</p>
<p>&#x540C;&#x5BF9;&#x6570;&#x51E0;&#x7387;&#x51FD;&#x6570;</p>
</li>
<li><p>Page58: &#x5BF9;&#x7387;&#x56DE;&#x5F52;(132,325)(logistic regression)</p>
<p>&#x7528;&#x7EBF;&#x6027;&#x56DE;&#x5F52;&#x6A21;&#x578B;&#x7684;&#x9884;&#x6D4B;&#x7ED3;&#x679C;&#x53BB;&#x903C;&#x8FD1;&#x771F;&#x5B9E;&#x6807;&#x8BB0;&#x7684;&#x5BF9;&#x6570;&#x51E0;&#x7387;</p>
</li>
<li><p>Page58: &#x5BF9;&#x6570;&#x51E0;&#x7387;&#x51FD;&#x6570;(98)&#xFF08;logistic function&#xFF09;</p>
<p>&#x89C1;&#x5BF9;&#x6570;&#x51E0;&#x7387;&#x56DE;&#x5F52;</p>
</li>
<li><p>Page58: &#x51E0;&#x7387;(odds)</p>
<p>&#x82E5;&#x5C06;&#x6A21;&#x578B;&#x8F93;&#x51FA;y&#x89C6;&#x4E3A;&#x6837;&#x672C;x&#x4F5C;&#x4E3A;&#x6B63;&#x4F8B;&#x7684;&#x53EF;&#x80FD;&#x6027;&#xFF0C;&#x5219;1-y&#x662F;&#x5176;&#x53CD;&#x4F8B;&#x53EF;&#x80FD;&#x6027;&#xFF0C;&#x4E24;&#x8005;&#x7684;&#x6BD4;&#x503C;y/1-y&#x79F0;&#x4E3A;&#x51E0;&#x7387;</p>
</li>
<li><p>Page58: &#x66FF;&#x4EE3;&#x51FD;&#x6570;&#xFF08;surrogate function&#xFF09;</p>
<p>&#x529F;&#x80FD;&#x76F8;&#x4F3C;&#x7684;&#x51FD;&#x6570;&#xFF0C;&#x4F8B;&#x5982;&#x7528;&#x5BF9;&#x6570;&#x51E0;&#x7387;&#x51FD;&#x6570;&#x66FF;&#x4EE3;&#x5355;&#x4F4D;&#x9636;&#x8DC3;&#x51FD;&#x6570;</p>
</li>
<li><p>Page59: &#x5BF9;&#x6570;&#x4F3C;&#x7136;(149)&#xFF08;log-likelihood&#xFF09;</p>
<p><script type="math/tex; ">l(w,b) = \sum_i^n ln p(y_i|x_i;w,b)</script></p>
<p>&#x5BF9;&#x7387;&#x56DE;&#x5F52;&#x6A21;&#x578B;&#x6700;&#x5927;&#x5316;&#x5BF9;&#x6570;&#x4F3C;&#x7136;&#xFF0C;&#x5373;&#x4EE4;&#x6BCF;&#x4E2A;&#x6837;&#x672C;&#x5C5E;&#x4E8E;&#x5176;&#x771F;&#x5B9E;&#x6807;&#x8BB0;&#x7684;&#x6982;&#x7387;&#x8D8A;&#x5927;&#x8D8A;&#x597D;</p>
</li>
<li><p>Page59: &#x6781;&#x5927;&#x4F3C;&#x7136;&#x6CD5;(149,297)(maximum likelihood method)</p>
<p>&#x4F30;&#x8BA1;&#x7C7B;&#x6761;&#x4EF6;&#x6982;&#x7387;&#x7684;&#x4E00;&#x79CD;&#x5E38;&#x7528;&#x7B56;&#x7565;&#x662F;&#x5148;&#x5047;&#x5B9A;&#x5176;&#x5177;&#x6709;&#x67D0;&#x79CD;&#x786E;&#x5B9A;&#x7684;&#x6982;&#x7387;&#x5206;&#x5E03;&#x5F62;&#x5F0F;&#xFF0C;&#x518D;&#x57FA;&#x4E8E;&#x8BAD;&#x7EC3;&#x6837;&#x672C;&#x5BF9;&#x6982;&#x7387;&#x5206;&#x5E03;&#x7684;&#x53C2;&#x6570;&#x8FDB;&#x884C;&#x4F30;&#x8BA1;&#x3002;</p>
</li>
<li><p>Page60: Fisher&#x5224;&#x522B;&#x5206;&#x6790;(Fisher Discriminant Analysis)</p>
<p>&#x540C;&#x7EBF;&#x6027;&#x5224;&#x522B;&#x5206;&#x6790;</p>
</li>
<li><p>Page60: &#x7EBF;&#x6027;&#x5224;&#x522B;&#x5206;&#x6790;(139)&#xFF08;Linear Discriminant Analysis&#xFF09;</p>
<p>&#x7ED9;&#x5B9A;&#x8BAD;&#x7EC3;&#x6837;&#x4F8B;&#x96C6;&#xFF0C;&#x8BBE;&#x6CD5;&#x5C06;&#x6837;&#x4F8B;&#x6295;&#x5F71;&#x5230;&#x4E00;&#x6761;&#x76F4;&#x7EBF;&#x4E0A;&#xFF0C;&#x4F7F;&#x5F97;&#x540C;&#x7C7B;&#x6837;&#x4F8B;&#x7684;&#x6295;&#x5F71;&#x5C3D;&#x53EF;&#x80FD;&#x63A5;&#x8FD1;&#xFF0C;&#x5F02;&#x7C7B;&#x6837;&#x4F8B;&#x7684;&#x6295;&#x5F71;&#x70B9;&#x5C3D;&#x53EF;&#x80FD;&#x8FDC;&#x79BB;&#xFF0C;&#x5728;&#x5BF9;&#x65B0;&#x6837;&#x672C;&#x8FDB;&#x884C;&#x5206;&#x7C7B;&#x65F6;&#xFF0C;&#x5C06;&#x5176;&#x6295;&#x5F71;&#x5230;&#x540C;&#x6837;&#x7684;&#x8FD9;&#x6761;&#x76F4;&#x7EBF;&#x4E0A;&#xFF0C;&#x518D;&#x6839;&#x636E;&#x6295;&#x5F71;&#x70B9;&#x7684;&#x4F4D;&#x7F6E;&#x6765;&#x786E;&#x5B9A;&#x6837;&#x672C;&#x7684;&#x7C7B;&#x522B;&#x3002;</p>
</li>
<li><p>Page61: &#x5E7F;&#x4E49;&#x745E;&#x5229;&#x5546;&#xFF08;generalized Rayleigh quotient&#xFF09;</p>
<p>LDA&#x6B32;&#x6700;&#x5927;&#x5316;&#x7684;&#x76EE;&#x6807;&#xFF0C;&#x5373;Sb(&#x7C7B;&#x95F4;&#x6563;&#x5EA6;&#x77E9;&#x9635;)&#xFF0C;Sw(&#x7C7B;&#x5185;&#x6563;&#x5EA6;&#x77E9;&#x9635;)&#x7684;&#x5E7F;&#x4E49;&#x745E;&#x5229;&#x5546;</p>
</li>
<li><p>Page61: &#x7C7B;&#x95F4;&#x6563;&#x5EA6;&#x77E9;&#x9635;(138)(within-class scatter matrix)</p>
<p>&#x5404;&#x7C7B;&#x6837;&#x672C;&#x5185;&#x90E8;&#x6C42;&#x5DEE;&#x5E73;&#x65B9;&#xFF0C;&#x518D;&#x6C42;&#x548C;</p>
</li>
<li><p>Page61: &#x7C7B;&#x5185;&#x6563;&#x5EA6;&#x77E9;&#x9635;(138)(between-class scatter matrix)</p>
<p>&#x5404;&#x7C7B;&#x6837;&#x672C;&#x4E4B;&#x95F4;&#x7684;&#x5747;&#x503C;&#x4E4B;&#x5DEE;&#x7684;&#x5E73;&#x65B9;&#x548C;</p>
</li>
<li><p>Page62: &#x5168;&#x5C40;&#x6563;&#x5EA6;&#x77E9;&#x9635;&#xFF08;global scatter matrix&#xFF09;</p>
<p>&#x6837;&#x672C;&#x4E0E;&#x5168;&#x5C40;&#x5747;&#x503C;&#x4E4B;&#x5DEE;&#x7684;&#x5E73;&#x65B9;&#x548C;</p>
</li>
<li><p>Page63: MvM&#xFF08;Many vs. Many&#xFF09;</p>
<p>&#x591A;&#x5206;&#x7C7B;&#x8F6C;&#x4E8C;&#x5206;&#x7C7B;&#x7684;&#x4E00;&#x79CD;&#x89E3;&#x51B3;&#x65B9;&#x6CD5;&#xFF1A;&#x6BCF;&#x6B21;&#x5C06;&#x82E5;&#x5E72;&#x4E2A;&#x7C7B;&#x4F5C;&#x4E3A;&#x6B63;&#x7C7B;&#xFF0C;&#x82E5;&#x5E72;&#x4E2A;&#x5176;&#x4ED6;&#x7C7B;&#x4F5C;&#x4E3A;&#x53CD;&#x7C7B;&#xFF0C;&#x901A;&#x5E38;&#x7528;&#x7EA0;&#x9519;&#x8F93;&#x51FA;&#x7801;ECOC&#x6765;&#x62C6;&#x5206;&#x3002;</p>
</li>
<li><p>Page63: OVO&#xFF08;one vs. one&#xFF09;</p>
<p>&#x4E00;&#x5BF9;&#x4E00;&#xFF0C;&#x5BF9;&#x4E8E;&#x591A;&#x4E2A;&#x5206;&#x7C7B;&#xFF0C;&#x4E24;&#x4E24;&#x914D;&#x5BF9;&#x4EA7;&#x751F;N(N-1)/2&#x4E2A;&#x4E8C;&#x5206;&#x7C7B;&#x4EFB;&#x52A1;</p>
</li>
<li><p>Page63: OvR(one vs. Rest)</p>
<p>&#x4E00;&#x5BF9;&#x591A;&#xFF0C;&#x6BCF;&#x6B21;&#x5C06;&#x4E00;&#x4E2A;&#x7C7B;&#x7684;&#x6837;&#x4F8B;&#x4F5C;&#x4E3A;&#x6B63;&#x4F8B;&#xFF0C;&#x6240;&#x6709;&#x5176;&#x4ED6;&#x7C7B;&#x7684;&#x6837;&#x4F8B;&#x4F5C;&#x4E3A;&#x53CD;&#x4F8B;&#x6765;&#x8BAD;&#x7EC3;N&#x4E2A;&#x5206;&#x7C7B;&#x5668;&#x3002;</p>
</li>
<li><p>Page63: &#x591A;&#x5206;&#x7C7B;&#x5668;&#x5B66;&#x4E60;</p>
<p>&#x987E;&#x540D;&#x601D;&#x4E49;&#x3002;&#x3002;</p>
</li>
<li><p>Page64: ECOC</p>
<p>&#x540C;&#x7EA0;&#x9519;&#x8F93;&#x51FA;&#x7801;</p>
</li>
<li><p>Page64: &#x7EA0;&#x9519;&#x8F93;&#x51FA;&#x7801;&#xFF08;Error Correcting Output Codes&#xFF09;</p>
<p>&#x5C06;&#x7F16;&#x7801;&#x601D;&#x60F3;&#x5F15;&#x5165;&#x7C7B;&#x522B;&#x62C6;&#x5206;&#xFF0C;&#x5206;&#x7F16;&#x7801;&#x548C;&#x89E3;&#x7801;&#x4E24;&#x90E8;&#xFF1A;</p>
<ul>
<li>&#x7F16;&#x7801;&#xFF1A;&#x5BF9;N&#x4E2A;&#x5206;&#x7C7B;&#x5668;&#x505A;M&#x6B21;&#x5212;&#x5206;&#xFF0C;&#x6BCF;&#x6B21;&#x5212;&#x5206;&#x5C06;&#x4E00;&#x90E8;&#x5206;&#x7C7B;&#x522B;&#x5212;&#x4E3A;&#x6B63;&#x7C7B;&#xFF0C;&#x5176;&#x4F59;&#x4E3A;&#x53CD;&#x7C7B;&#xFF0C;&#x4E00;&#x5171;&#x4EA7;&#x751F;M&#x4E2A;&#x4E8C;&#x5206;&#x7C7B;&#x8BAD;&#x7EC3;&#x96C6;&#xFF0C;&#x8BAD;&#x7EC3;&#x51FA;M&#x4E2A;&#x5206;&#x7C7B;&#x5668;</li>
<li>&#x89E3;&#x7801;&#xFF1A;M&#x4E2A;&#x5206;&#x7C7B;&#x5668;&#x5206;&#x522B;&#x5BF9;&#x6D4B;&#x8BD5;&#x6837;&#x672C;&#x505A;&#x9884;&#x6D4B;&#xFF0C;&#x6240;&#x6709;&#x9884;&#x6D4B;&#x6807;&#x8BB0;&#x7EC4;&#x6210;&#x4E00;&#x4E2A;&#x7F16;&#x7801;&#xFF0C;&#x5C06;&#x8FD9;&#x4E2A;&#x9884;&#x6D4B;&#x7F16;&#x7801;&#x4E0E;&#x6BCF;&#x4E2A;&#x7C7B;&#x522B;&#x5404;&#x81EA;&#x7684;&#x7F16;&#x7801;&#x505A;&#x6BD4;&#x8F83;&#xFF0C;&#x8FD4;&#x56DE;&#x5176;&#x4E2D;&#x8DDD;&#x79BB;&#x6700;&#x5C0F;&#x7684;&#x7C7B;&#x522B;&#x4F5C;&#x4E3A;&#x6700;&#x7EC8;&#x9884;&#x6D4B;&#x7ED3;&#x679C;&#x3002;</li>
</ul>
</li>
<li><p>Page65: &#x7F16;&#x7801;&#x77E9;&#x9635;(coding Matrix)</p>
<p>ECOC&#x4E2D;&#xFF0C;&#x7C7B;&#x522B;&#x5212;&#x5206;&#x901A;&#x8FC7;&#x7F16;&#x7801;&#x77E9;&#x9635;&#xFF08;&#x7F16;&#x7801;&#x7EC4;&#x6210;&#x7684;&#x77E9;&#x9635;&#x3002;&#x3002;&#xFF09;&#x6307;&#x5B9A;&#x3002;</p>
</li>
<li><p>Page66: &#x7C7B;&#x522B;&#x4E0D;&#x5E73;&#x8861;(209)&#xFF08;class-imbalance&#xFF09;</p>
<p>&#x5206;&#x7C7B;&#x4EFB;&#x52A1;&#x4E2D;&#x4E0D;&#x540C;&#x7C7B;&#x522B;&#x7684;&#x8BAD;&#x7EC3;&#x6837;&#x4F8B;&#x6570;&#x76EE;&#x5DEE;&#x522B;&#x5F88;&#x5927;&#x7684;&#x60C5;&#x51B5;&#xFF0C;&#x5F80;&#x5F80;&#x901A;&#x8FC7;&#x518D;&#x7F29;&#x653E;&#x5904;&#x7406;&#x3002;</p>
</li>
<li><p>Page67: &#x8FC7;&#x91C7;&#x6837;&#xFF08;oversampling&#xFF09;</p>
<p>&#x5BF9;&#x8BAD;&#x7EC3;&#x96C6;&#x91CC;&#x7684;&#x67D0;&#x7C7B;&#x6837;&#x4F8B;&#x589E;&#x52A0;&#x91C7;&#x6837;&#x6B21;&#x6570;&#x51CF;&#x5C0F;&#x7C7B;&#x522B;&#x4E0D;&#x5E73;&#x8861;&#x3002;</p>
</li>
<li><p>Page67: &#x6B20;&#x91C7;&#x6837;(undersampling)</p>
<p>&#x5BF9;&#x8BAD;&#x7EC3;&#x96C6;&#x91CC;&#x7684;&#x67D0;&#x7C7B;&#x6837;&#x4F8B;&#x51CF;&#x5C11;&#x91C7;&#x6837;&#x6B21;&#x6570;&#x51CF;&#x5C0F;&#x7C7B;&#x522B;&#x4E0D;&#x5E73;&#x8861;&#x3002;</p>
</li>
<li><p>Page67: &#x4E0A;&#x91C7;&#x6837;(upsampling)</p>
<p>&#x540C;&#x8FC7;&#x91C7;&#x6837;</p>
</li>
<li><p>Page67: &#x7A00;&#x758F;&#x8868;&#x793A;(255)&#xFF08;sparse representation&#xFF09;</p>
<p>&#x89C1;11&#x7AE0;&#x3002;</p>
</li>
<li><p>Page67: &#x7A00;&#x758F;&#x6027;(sparsity)</p>
<p>&#x672C;&#x8D28;&#x4E0A;&#x5BF9;&#x5E94;L0&#x8303;&#x6570;&#x7684;&#x4F18;&#x5316;&#x3002;</p>
</li>
<li><p>Page67: &#x4E0B;&#x91C7;&#x6837;(downsampling)</p>
<p>&#x540C;&#x6B20;&#x91C7;&#x6837;</p>
</li>
<li><p>Page67: &#x9608;&#x503C;&#x79FB;&#x52A8;(threshold-moving)</p>
<p>&#x6B20;&#x91C7;&#x6837;&#x548C;&#x8FC7;&#x91C7;&#x6837;&#x6539;&#x53D8;&#x4E86;&#x89C2;&#x6D4B;&#x51E0;&#x7387;&#xFF0C;&#x5728;&#x6267;&#x884C;&#x5728;&#x7F29;&#x653E;&#x65F6;&#xFF0C;&#x6839;&#x636E;&#x91C7;&#x6837;&#x6BD4;&#x4F8B;&#x8C03;&#x6574;&#x9608;&#x503C;&#x3002;</p>
</li>
<li><p>Page67: &#x518D;&#x5E73;&#x8861;(rebalance)</p>
<p>&#x540C;&#x518D;&#x7F29;&#x653E;</p>
</li>
<li><p>Page67: &#x518D;&#x7F29;&#x653E;(rescaling)</p>
<p>&#x539F;&#x672C;&#x51B3;&#x7B56;&#x89C4;&#x5219;&#x662F;<script type="math/tex; ">y/(1-y)>1</script>&#x9884;&#x6D4B;&#x4E3A;&#x6B63;&#xFF0C;&#x5373;&#x9884;&#x6D4B;&#x4E3A;&#x6B63;&#x7684;&#x53EF;&#x80FD;&#x6027;&#x5927;&#x4E8E;&#x9884;&#x6D4B;&#x4E3A;&#x8D1F;&#x7684;&#x53EF;&#x80FD;&#x6027;&#xFF0C;&#x4F46;&#x6B63;&#x4F8B;&#x5C11;&#x7684;&#x65F6;&#x5019;&#xFF0C;&#x6211;&#x4EEC;&#x53EF;&#x4EE5;&#x4FEE;&#x6539;&#x4E3A;&#xFF0C;&#x9884;&#x6D4B;&#x4E3A;&#x6B63;&#x7684;&#x53EF;&#x80FD;&#x6027;&#x9AD8;&#x4E8E;&#x89C2;&#x6D4B;&#x5230;&#x7684;&#x51E0;&#x7387;&#xFF0C;&#x5373;<script type="math/tex; ">y/(1-y) > m^+/m^-</script></p>
</li>
<li><p>Page68: &#x591A;&#x6807;&#x8BB0;&#x5B66;&#x4E60;(multi-label learning)</p>
<p>&#x4F8B;&#x5982;&#x4E00;&#x5E45;&#x753B;&#x53EF;&#x540C;&#x65F6;&#x6807;&#x6CE8;&#x84DD;&#x5929;&#xFF0C;&#x767D;&#x4E91;&#xFF0C;&#x7F8A;&#x7FA4;&#x7B49;&#xFF0C;&#x6BCF;&#x4E2A;&#x6837;&#x672C;&#x5C5E;&#x4E8E;&#x591A;&#x4E2A;&#x7C7B;&#x522B;&#xFF0C;&#x8FD9;&#x5C31;&#x662F;&#x591A;&#x6807;&#x8BB0;&#x5B66;&#x4E60;&#x3002;</p>
</li>
</ul>

                                
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